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Akshay Bharadwaj Kunigal Harish
Mid-level Machine Learning Engineer specializing in NLP, computer vision, and LLM systems
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About
Built a production multi-agent cybersecurity defense simulator orchestrated with CrewAI, combining Red/Blue team LLM agents, a RAG runbook retriever, and an RL remediation agent trained via state-space simplification and reward shaping for rapid incident response. Also partnered with quant analysts and fund managers to deliver an automated trading and portfolio management system using statistical methods plus CNN/LSTM models, reporting up to 15% weekly ROI.
Experience
Education
Key Strengths
- Built and deployed a multi-agent cybersecurity defense simulator combining LLM agents, RAG, and an RL remediation agent
- Improved RL learning by reducing state space from 100+ to 18 states and making action-outcome simulation deterministic
- Designed reward shaping for time-critical incident response (bonus for fast response, penalty for delays)
- Strong experimentation and evaluation discipline (Q-table inspection, reward tracking, convergence and success-rate analysis, learning-curve visualization)
- Translates non-technical stakeholder needs into AI-driven products (worked with quant analysts and fund managers)
- Delivered automated trading/portfolio system reported to achieve up to 15% weekly ROI
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